Abstract 3628: Comprehensive identification of lineage associated cancer genes in 122 histologies
Authors: Chaitanya Bandlamudi, Walid K. Chatila, Shaleigh A. Smith, Subhiksha Nandakumar, Craig Bielski, Bastien Nguyen, Henry S. Walch, Christoph K. Kreitzer, Kanika S. Arora, Tran Thinh Ngoc, Miika Mehine, Irina Ostrovnaya, Ino de Bruijn, Hyung Jun Woo, Ritika Kundra, Christopher J. Fong, Satshil Rana, Gaofei Zhao, Mingxuan Zhang, Mark R. Zucker, Hongxin Zhang, Ryan Ptashkin, Rose Brannon, Eduard Reznik, JianJiong Gao, Maria E. Arcila, Ryma Benayed, Debyani Chakravarty, David Solit, Mark T. Donoghue, Marc Ladanyi, Nikolaus D. Schultz, Michael F. Berger, Ahmet Zehir
Journal: Cancer Research (2022)

Abstract Although the majority of cancer genes show a high degree of specificity for certain lineages, genomic profiling of cancer patients routinely identify alterations in genes that are atypical to the presented cancer type but are canonical drivers in a different lineage. It is often unclear if these atypical drivers arose early in tumorigenesis or were acquired during progression. A complete understanding of lineage associated genes (LAGs) will enable better interpretation of the molecular etiology of each diagnosed tumor. Here, we used a cohort of 38,912 patients across 122 cancer histologies (each with 50 or more patients) profiled for somatic alterations (mutations, copy number alterations and gene fusions) using the MSK-IMPACT assay. Tumors with TMB &amp;gt; 15 were already excluded. All alterations were classified as drivers using OncoKB. Allele-specific copy number calls were assessed using FACETS. Overall, 95% of patients harbored at least one oncogenic alteration, with a median of 4 drivers per tumor. We observed widespread prevalence of drivers across lineages with each gene mutated in a median of 36 different lineages. Conversely, a median of 103 genes were mutated at least once in each lineage. Hypothesizing that cancer genes are influenced by cell of origin, we sought to identify lineages harboring significantly higher rates of drivers in a given gene compared to its pancancer driver rate. We identified 1781 significant (adjusted P &amp;lt; 0.05) gene and lineage associations, and an additional 109 involving genes mutated at &amp;gt;10% in the respective lineages but which did not reach significance were also included. Lineage-agnostic genes such as TP53 and CDKN2A were associated with a broad spectrum of lineages (90 and 55, respectively). However, overall, each gene we profiled was found to be associated with a median of 3 distinct lineages. For example, while BRAF drivers are found in nearly all histologies (n=91), it is enriched for drivers in only 8 lineages: melanoma (acral and cutaneous), thyroid (poorly differentiated, anaplastic and papillary) and bowel (mucinous adenocarc. of colon/rectum, colon adenocarc. and neuroendocrine carc. of colon/rectum). In all, nearly a third of all drivers were observed in non-associated lineages. We next compared the somatic properties of drivers among genes in associated lineages vs. the same genes in non-associated lineages. We observed that mutations in LAGs were more often clonal (83% vs. 73%, associated vs. non-associated, P = 0) and showed enrichment for mutant allele imbalance in oncogenes (40% vs. 23%, P = 2e-111) and biallelic inactivation in tumor suppressor LAGs (71% vs. 58%, P = 4e-130). Furthermore, 93% of all OncoKB Level 1/2/3A actionable alterations, which are classified based on their histology, were in LAGs. In conclusion, our findings enable classification of drivers that are relevant for lineage-specific malignant transformation and advance our understanding of tumor biology. Citation Format: Chaitanya Bandlamudi, Walid K. Chatila, Shaleigh A. Smith, Subhiksha Nandakumar, Craig Bielski, Bastien Nguyen, Henry S. Walch, Christoph K. Kreitzer, Kanika S. Arora, Tran Thinh Ngoc, Miika Mehine, Irina Ostrovnaya, Ino de Bruijn, Hyung Jun Woo, Ritika Kundra, Christopher J. Fong, Satshil Rana, Gaofei Zhao, Mingxuan Zhang, Mark R. Zucker, Hongxin Zhang, Ryan Ptashkin, Rose Brannon, Eduard Reznik, JianJiong Gao, Maria E. Arcila, Ryma Benayed, Debyani Chakravarty, David Solit, Mark T. Donoghue, Marc Ladanyi, Nikolaus D. Schultz, Michael F. Berger, Ahmet Zehir. Comprehensive identification of lineage associated cancer genes in 122 histologies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3628.